Research on Automatic Speech Recognition for dysarthric speech
The effect of speech pathology on automatic speaker verification
Animate a 3D tongue based on a physics simulation of muscles and pressure.
classify dysarthria severity in ALS patients.
User guide, tutorial videos, presentations, logos and artwork, for an Augmentative and Alternative Communication (AAC) application, intended to be used by people suffering from speech impairments such as apraxia and/or dysarthria of speech.
Cross-platform application, developed in Flutter, for mobile phones, watches and tablets, for an Augmentative and Alternative Communication (AAC) application, intended to be used by people suffering from speech impairments such as apraxia and/or dysarthria of speech.
A machine learning-based system for detecting and transcribing dysarthric speech, utilizing the TORGO dataset, advanced speech processing techniques, and a user-friendly Streamlit interface to enhance accessibility for individuals with speech impairments.
Web page for the project, privacy policy and terms and conditions, for an Augmentative and Alternative Communication (AAC) application, intended to be used by people suffering from speech impairments such as apraxia and/or dysarthria of speech.
A project to classify dysarthric and non-dysarthric speech using deep learning techniques.
This is the code belonged to the team working on the project in CCCN lab, Bangkok. This code is open to the public use with permission to primary author. Citation to the attached paper is required for all further publications.
Multilingual Audio-Based detection and voice restoration of Dysarthria using machine learning and signal processing techniques.
Korean jamo-level STT baseline for dysarthria assessment research
Add a description, image, and links to the dysarthria topic page so that developers can more easily learn about it.
To associate your repository with the dysarthria topic, visit your repo's landing page and select "manage topics."